A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion [Bulk RNA-seq]

Cellular conversion can be induced by perturbing a handful of key transcription factors (TFs). Replacement of direct manipulation of key TFs with chemical compounds offers a less laborious and safer strategy to drive cellular conversion for regenerative medicine. Nevertheless, identifying optimal chemical compounds currently requires large-scale screening of chemical libraries, which is resource-intensive. Existing computational methods aim at predicting cell conversion TFs, however there are no methods for identifying chemical compounds targeting these TFs. Here, we develop a single cell-based platform (SiPer) to systematically prioritize chemical compounds targeting desired TFs to guide cellular conversions. SiPer integrates a large compendium of chemical perturbations on non-cancer cells with a network model, and predicted known and novel chemical compounds in diverse cell conversion examples. Importantly, we applied SiPer to develop a highly efficient protocol for human hepatic maturation. Overall, SiPer provides a valuable resource to efficiently identify chemical compounds for cell conversion. Total of 7 samples were analyzed, which included primary human hepatocytes, human liver tissue, human hepatic progenitor-like cells, 2 samples of human induced hepatocytes cultured in Williams’ E medium with 2C (W2C) and 2 samples of Williams’ E medium with 6C (W6C). Global transcriptional profiles of these cells were analyzed by RNA-seq.